Closed ASL Interpreting for Online Videos
Matthew Seita · 2016 · ASSETS '16: Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/2982142.2982147
Summary
This paper introduces "closed interpreting"—a concept analogous to closed captions where an ASL interpreter video can be toggled on and customized alongside online video content. The motivation is straightforward but often overlooked: many deaf and hard of hearing people rely on American Sign Language as their primary language, making English captions insufficient or less accessible than sign language interpretation. The researcher developed and compared three implementations using a 15-minute mathematics lecture video: (1) Static closed interpreting, where the interpreter and lecture videos appear side-by-side in fixed positions; (2) Tracked interpreting, where the interpreter video automatically repositions to align horizontally with the relevant area of interest in the lecture (e.g., moving alongside where the instructor is writing); and (3) Customizable interpreting, which allows viewers to move, resize, adjust opacity (10-100%), and toggle the interpreter video on/off. Nineteen deaf and hard of hearing ASL users (12 Deaf, 7 hard of hearing, ages 20-29) participated in a counterbalanced study with eye tracking, rating each implementation on satisfaction, understanding, and ease of viewing using Likert scales.
Key findings
The customizable implementation scored significantly higher than the static implementation across all three measures (satisfaction, understanding, and ease of viewing) using Mann-Whitney U tests with Bonferroni correction (α = .0167). The tracked implementation also scored significantly higher than static for ease of viewing specifically. Participants rated the customization features favorably: the ability to move the interpreter received the highest rating (4.42/5), followed by resizing (4.31/5). The transparency/opacity adjustment feature was less well-received (3.42/5), suggesting that while positional and size control are valued, semi-transparent overlays may not be a priority preference. The results showed a consistent pattern of improvement from static → tracked → customizable implementations, though not all comparisons reached statistical significance. This suggests that both automated assistance (tracking relevant content) and user control (customization) contribute positively to the viewing experience. Eye tracking data was collected during the study, though detailed gaze analysis was not presented in this short paper, indicating potential for deeper analysis of how users visually attend to interpreter versus lecture content.
Relevance
This research highlights an important gap in video accessibility: the assumption that captions serve all deaf and hard of hearing viewers equally. For native ASL users—particularly those who acquired ASL as a first language or who have limited English literacy—sign language interpretation may be more accessible than text-based captions. This is especially relevant for educational content where comprehension is critical. The "closed interpreting" framing is valuable because it suggests a standardized, platform-level feature rather than ad-hoc solutions. Just as closed captions became a built-in feature of video platforms and television, closed interpreting could become an expected accessibility option. The customization findings provide concrete design guidance: interpreter windows should be movable and resizable, with toggle controls, and tracking features that follow content of interest. For content creators and platforms, the implication is that providing interpreter tracks as an alternative to or supplement for captions would better serve ASL-primary viewers. The technical implementation described (HTML-embedded synchronized videos) demonstrates that this is achievable with current web technologies without requiring specialized players.
Tags: deaf and hard of hearing · American Sign Language · video accessibility · closed interpreting · multimedia accessibility · sign language interpreter · online learning